Without the actual scatterplot data, I can't provide a precise answer. However, you can determine the best prediction for the number of bottles sold based on how the points are clustered in relation to the number of customers.
Here’s how you might approach it:
- Look at the scatterplot and find the cluster of points that corresponds to around 64 customers.
- Determine the general trend of the data—does it seem linear, and if so, what is the slope?
- See which of the options (4949, 2929, 3939, 8888) falls in line with the number of bottles sold for that number of customers according to the trend.
If the trend appears to increase steadily, then typically, the prediction with the highest number of bottles sold might be the correct choice. Conversely, if the data shows that not many bottles are sold with higher customers, choose the lower numbers.
If you have access to the specific scatterplot, you can easily find the point that corresponds to 64 customers and read off the number of bottles sold.